The Internet has enabled new digital printing workflows that are distributed, media-less, and share knowledge resources. One new application in the commercial printing field is referred to as “variable data printing” (VDP), where a rich template is populated with different data for each copy, typically merged from a database or determined algorithmically. In variable data printing, pages may be created with an automated page layout system, which places objects within a page and automatically generates a page layout that is pleasing to a user.
Variable data printing examples include permission-based marketing, where each copy is personalized with a recipient name, and the contents are chosen based on parameters like sex, age, income, or ZIP code; do-it-yourself catalogs, where customers describe to an e-commerce vendor their purchase desires, and vendors create customer catalogs with their offerings for that desire; customized offers in response to a tender for bids, with specification sheets, white papers, and prices customized for the specific bid; insurance and benefit plans, where customers or employees receive a contract with their specific information instead of a set of tables from which they can compute their benefits; executive briefing materials; and comic magazines, where the characters can be adapted to various cultural or religious sensitivities, and the text in the bubbles can be printed in the language of the recipient.
In traditional printing, the final proof is inspected visually by the customer and approved. In variable data printing, each printed copy is different, and it is not practical to proof each copy. When there are small problems, like a little underflow or overflow, the elements or objects on a page can be slightly nudged, scaled, or cropped (in the case of images). When the overflow is larger, the failure can be fatal, because objects will overlap and may no longer be readable or discriminable because the contrast is too low. When pages are generated automatically and not proofed, gross visual discriminability errors can occur.
Similarly, when background and foreground colors are automatically selected from limited color palettes, color combinations can be generated which, due to insufficient contrast, make text unreadable for readers with color vision deficiencies, or even for those with normal color vision. In the case of images, they can sink into a background or become too inconspicuous. This problem can happen in marketing materials when objects receive indiscriminable color combinations. This problem can be very subtle. For example, corporations may change their color palettes. Marketing materials that have been generated at an earlier point in time may no longer comply with the current palette and create confusion in the customer. In a variable data printing job, older material that was generated based on an older version of a color palette, may be printed with substitute colors from an updated color palette, and two previously very different colors could be mapped into close colors, causing discriminability issues.
Previously, the discriminability of objects in a print was verified visually on a proof print. In the case of variable data printing, this task is too onerous to be practical, because each printed piece is different. An automated solution to this problem is desirable. There are tools to automatically build pleasing color palettes for electronic documents, but these tools apply to the authoring phase, not to the production phase. In particular, these tools do not check the discriminability of objects.